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https://github.com/kartikeya443/handgesture_detection_opencv
A Computer Vision based model trained on data sets of over 300 inputs for a particular gesture is able to detect and identify human hands gestures effortlessly and is able to track the coordinates for further modifications in its usage for controlling devices like mouse and windows (control features are in development).
https://github.com/kartikeya443/handgesture_detection_opencv
deep-learning mediapipe numpy opencv tensorflow
Last synced: 9 days ago
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A Computer Vision based model trained on data sets of over 300 inputs for a particular gesture is able to detect and identify human hands gestures effortlessly and is able to track the coordinates for further modifications in its usage for controlling devices like mouse and windows (control features are in development).
- Host: GitHub
- URL: https://github.com/kartikeya443/handgesture_detection_opencv
- Owner: kartikeya443
- License: mit
- Created: 2024-01-19T06:32:33.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-02-29T12:09:57.000Z (9 months ago)
- Last Synced: 2024-02-29T13:33:57.958Z (9 months ago)
- Topics: deep-learning, mediapipe, numpy, opencv, tensorflow
- Language: Python
- Homepage:
- Size: 1.9 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Note: This model is trained and tested for 7 gestures at present. These are:
1. A, B, C (American Sign Language)
2. Hello (open hand with palm facing to the camera)
3. Love (hand with index finger and thumb crossed)
4. Yes (thumb's up)
5. No (thumb's down)
## Run Application
1. **_Install project dependencies_**
```sh
pip install -r requirements.txt
```
2. **_Run the application_**
```sh
python testing.py
```
## Reference images:
